ELM DE

说明：  用基带等效的方式仿真16-QAM在AWGN信道下的误码率和误比特率性能，并与理论值相比较。(The bit error rate (BER) and bit error rate (BER) performance of 16-QAM in AWGN channel is simulated by baseband equivalent method, and compared with the theoretical value.)

matlab 主成分分析法程序，以目标威胁度评估为例(matlab principal component analysis procedures in order to target the threat assessment as an example)

小世界网络模型的m.文件 可生成网络矩阵或者邻接矩阵(M. small-world network model file to generate the network matrix or adjacency matrix)

Rake接收机蒙特卡洛仿真，扩频+3径瑞利信道 三种分集合并方式对比(Rake receiver, Monte Carlo simulation, 3 paths Rayleigh channel Three kinds of collection and means of contrasts)

关于拉曼光纤激光器超连续谱的仿真程序，欢迎大家下载楼！(this is about supercontinue spectrum.)

fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples. fits data to the probability of the form: p(r) = sqrt(2/pi)*(a^(-3/2))*(r^2)*exp(-(r^2)/(2*a)) with parameter: a format: result = fit_maxwell_pdf( x,y,W,hAx ) input: y - vector, samples of the histogram to be fitted x - vector, position of the samples of the histogram (i.e. y = f(x,a)) W - matrix or scalar, a square weighting matrix of the size NxN where N = length(y), or 0 to indicate no weighting is needed. hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields a - fitted parameter VAR - variance of the estimation type- weighted LS or not weighted LS iter- number of iteration for the solution

这个是对于fir带通滤波器以及iir低通滤波器的一个仿真。程序代码通俗易懂，意义很大。(This is a band-pass filter and the fir iir low-pass filter with a simulation. Program code easy to understand, very meaningful.)

matlab code for bitstuffing in HDLC protocol

说明：  本文使用了两种方法优化matlab的程序，缩短了算法的时间。方法1：使用Optimization Toolbox中的并行优化；不需要修改代码。方法2：增加一行代码，即可优化(Improving Optimization Performance with Parallel Computing)

通过遗传算法计算下列函数的全局最优值 y(t)=sum(x(t,:).*x(t,:))(Global calculate the following functions by genetic algorithms optimal value y(t)=sum(x(t,:).*x(t,:)) )